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| Authors: | Jouni Helske | ||||
| Title: | KFAS: Exponential Family State Space Models in R | ||||
| Abstract: | State space modeling is an efficient and flexible method for statistical inference of a broad class of time series and other data. This paper describes the R package KFAS for state space modeling with the observations from an exponential family, namely Gaussian, Poisson, binomial, negative binomial and gamma distributions. After introducing the basic theory behind Gaussian and non-Gaussian state space models, an illustrative example of Poisson time series forecasting is provided. Finally, a comparison to alternative R packages suitable for non-Gaussian time series modeling is presented. | ||||
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Page views:: 2379. Submitted: 2015-05-06. Published: 2017-06-09. |
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| Paper: |
KFAS: Exponential Family State Space Models in R
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| DOI: |
10.18637/jss.v078.i10
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This work is licensed under the licenses Paper: Creative Commons Attribution 3.0 Unported License Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license. |